System and method for vehicle speed monitoring using historical speed data

ABSTRACT

A target (not-to-exceed) speed for a vehicle over a road segment ahead of the vehicle is established based on a desired relationship with a speed profile of the segment. The speed profile is generated by analyzing a statistical distribution of historical speed data over the segment collected by probe vehicles. A driver alert is activated if the vehicle is likely to exceed the target speed based on at least one measured vehicle dynamic property. The target speed may be established by identifying a baseline road segment over which the vehicle has previously travelled and which is similar to the approaching road segment, comparing a past speed of the vehicle over the baseline segment with a speed profile of the baseline segment to determine a speed differential, and applying the speed differential to the speed profile of the approaching segment.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a division of U.S. application Ser. No. 12/794,841filed Jun. 7, 2010, now U.S. Pat. No. 8,478,499 B2, the disclosure ofwhich is incorporated in its entirety by reference herein.

TECHNICAL FIELD

This invention relates to a speed monitoring system for an automotivevehicle, and more specifically to such a system that establishes adesired speed based on historical speed data for a particular segment ofroad.

BACKGROUND

It is known to provide the driver of an automotive vehicle with awarning or advisory if the vehicle exceeds a desired maximum speed. Insome systems, the desired or allowable maximum speed may be based onlegally-set speed limit data stored, for example, in a digital map, orusing artificial vision systems to read speed limit signs posted alongthe route of travel. Other proposed systems use wireless (for exampleradio frequency or infrared) systems to transmit signals that arereceived by equipment aboard the vehicle to indicate a speed limit ordesired speed.

It is further known to calculate a maximum safe or recommended speed tobe driven around an approaching curve and issue a warning if the vehicleexceeds (or is predicted to exceed) that speed. Such methods generallyconsider the road geometry, primarily the radius of curvature, todetermine the recommended speed. U.S. patent application Ser. No.12/712,446 filed Feb. 25, 2010, and assigned to the assignee of thepresent application, discloses such methods, and the disclosure isincorporated herein by reference. However, there are many factors otherthan road geometry that influence how fast a particular vehicle, asdriven by a particular driver, may safely and comfortably negotiate acurve. These other factors may include a driver's particular experiencelevel, road surface conditions, merging traffic lanes, and weatherconditions.

U.S. Pat. No. 7,479,897 discloses a method of predicting an imminentvehicle rollover situation for heavy trucks driving around relativelysharp curves such as freeway exit/entrance ramps. The method includesbuilding an accurate digital map of roadways, including a road surfacebank angle and radius of curvature at each point on the roadway, usingdata gathered from a fleet of vehicles equipped with GPS trackingsystems. A maximum safe speed is then calculated for each data pointbased on a calculated lateral acceleration the truck will experiencewhen rounding a curve of that bank and curvature. The '897 referencefurther discusses calculating a speed distribution for each point alonga roadway from data gathered by trucks that have previously driven overthe road. This historical speed data is used to predict the likelihoodthat the truck will exceed the maximum safe speed when it reaches theup-coming curve by examining the relationship between the truck'scurrent speed and the historical speed distribution (percentile) for itscurrent point on the road. This method requires data-intensivemeasurement of road geometry in order to accurately calculate roadcurvature and bank angle.

Digital map data bases for use in vehicle navigation systems are wellknown and are evolving to contain GPS data collected by so-called probevehicles. A probe vehicle is any vehicle equipped with appropriate GPSand related communication systems that allow the vehicle to transmitdata to a remote collection point. The probe vehicles together serve asa data collection fleet. The data collected by probe vehicles mayinclude latitude, longitude, absolute time, position error estimate, andvehicle speed. This data may be referenced to an existing map data baseto permit roads to be subsequently queried to determine expected speedover a road or a segment thereof. Tele Atlas® is a digital mappingcompany that utilizes probe vehicle data for driving purposes. TeleAtlas® advertises that it generates speed profiles for road segmentsthat are derived from aggregating and processing hundreds of billions ofanonymous GPS measurements from millions of probe vehicles to reflectactual consumer driving patterns. This data helps determine realisticaverage road way speeds for different times of day and different days ofthe week.

SUMMARY

According to a described embodiment, the speed of an automotive vehicleis monitored and a vehicle system, such as a warning device, isactivated if the vehicle speed is expected to exceed a target speed overan approaching road segment lying ahead of the vehicle. A speed profileof the approaching segment is accessed, the speed profile beinggenerated by analyzing a statistical distribution of historical speeddata collected from probe vehicles that have previously travelled overthe approaching segment. The target speed is established based on adesired relationship with the speed profile, the desired relationshipbeing based upon at least one of a driver condition factor, a drivingconditions factor, a vehicle condition factor, and a driver inputfactor. The likelihood that the vehicle will exceed the target speed isassessed based, at least in part, on at least one measured vehicledynamic property.

According to another described embodiment, the target speed isestablished by identifying a baseline road segment over which thevehicle has previously travelled, comparing a past speed of the vehicleover the baseline segment with a speed profile of the baseline segment,and applying the speed differential to the first speed profile. Thebaseline road segment may be selected based upon similarity to theapproaching road segment in at least one of a curvature, an incline, abank angle, a camber, a surface quality, and a posted speed limit.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 is a schematic depiction of a section of road divided intosegments and depicting speed profiles for each segment;

FIG. 2 is a sample of a speed histogram for a road segment;

FIG. 3 is a simplified process flow diagram of a method for speedadvisory determination;

FIG. 4 is a simplified process diagram of a branch method from FIG. 3;

FIG. 5 is a simplified process diagram of an alternative branch methodfrom FIG. 3; and

FIG. 6 is a simplified functional block diagram of an embodiment of aspeed advisory system.

DETAILED DESCRIPTION

As required, detailed embodiments of the present invention are disclosedherein; however, it is to be understood that the disclosed embodimentsare merely exemplary of the invention that may be embodied in variousand alternative forms. The figures are not necessarily to scale; somefeatures may be exaggerated or minimized to show details of particularcomponents. Therefore, specific structural and functional detailsdisclosed herein are not to be interpreted as limiting, but merely as arepresentative basis for teaching one skilled in the art to variouslyemploy the present invention.

FIG. 1 is a schematic depiction of a length of roadway 10 divided intosix segments labeled A through F. Road segments may bedelineated/identified based upon a standard or uniform distance (every10 meters for example). Or, the segments may be based upon changes inone or more roadway characteristics such as radius of curvature, incline(uphill/downhill), bank angle, camber, road surface quality(rough/smooth, asphalt/concrete), and/or posted speed limit. Forexample, in FIG. 1 segments A, D, and E are considered to be relativelystraight, while segments B, C, and F are considered curved. Adjacentstraight segments D and E may be identified as separate segments due todifferences in one or more of the other characteristics mentioned above.

At least one historical speed profile is generated for each road segmentA-F, the speed profile based upon data collected from probe vehiclesthat have previously driven over the segment. In FIG. 1, historicalspeed profiles are identified as a through f related to road segments Athrough F respectively.

Each speed profile a-f is generated or calculated by statisticallyanalyzing the cumulative data gathered by the probe vehicles. The datamay be plotted graphically as shown in FIG. 2, showing the number ofvehicle trips over the segment for falling into given vehicle speedranges or bins. In the FIG. 2 embodiment, speed bins every 2 miles perhour are used for the plot. A statistical distribution may be determinedfrom the plot. For example, the FIG. 2 distribution may be identified asa normal distribution having a mean value and a standard deviation(sigma).

As discussed in the Background section above, historical vehicles speeddata may be collected from probe vehicles equipped with GPS trackingsystems so that every time a probe vehicle travels over a given segmentof road, its current speed is recorded and/or reported to a collectionsystem such as that operated by Tele Atlas®.

For each speed data point taken by a probe vehicle, it may be alsobeneficial to identify and record characteristics that are shown orbelieved to be correlated with the speed driven. Such characteristicsmay include time-of-day, day-of-week, and weather conditions. With thisinformation, multiple speed profiles may be generated or developed foreach road segment. Other multi-dimensional statistical analysis may beperformed if such is believed to provide a valuable statisticalanalysis.

FIG. 3 illustrates, in flow chart form, a method of monitoring the speedof a vehicle and identifying that the vehicle may be likely to exceed atarget speed on a road segment if no corrective action is taken. Themethod begins at block 100 and progresses to block 110 where the vehiclelocation is determined. This may be accomplished, for example, utilizinga GPS navigation system and map database, as is well known. Progressingto block 120, the vehicle location is compared with a map data base toidentify an approaching road segment, that is, a road segment that liesahead of the vehicle as it progresses along its current and/or plannedroute of travel.

At block 130, a speed profile for the approaching segment is accessed.The speed profile may be accessed by wireless communication with aremote database, or the speed profile may be stored onboard the vehiclein an appropriate data storage medium. If the speed profiles in thedatabase include data on any speed-correlated conditions such as thetime-of-day, day-of-week, and/or weather at the time the data weretaken, the current conditions may be considered so that the speedprofile accessed matches one or more of the current condition.

At block 140, a desired relationship between the speed profile accessedfor the approaching segment and the current vehicle (or vehicle/drivercombination) is determined. The desired relationship may, for example,be expressed in terms of a statistical deviation from a mean value. Ifthe speed profile is identified as having a normal distribution as inFIG. 2, the desired relationship may be that the vehicle should travelat a speed equal to the mean value for the road segment, or at a speedequal to one (or more) sigma above or below the mean value.

One method for determining the desired relationship is depicted in FIG.4. At step 210, the driver of the vehicle is prompted or otherwiseoffered the opportunity to select how fast, in relation to a speedprofile, he/she desires to drive on a particular trip. The driver maymake this decision and input at the beginning of a trip, for exampleimmediately prior to or after starting the vehicle or putting thevehicle into gear. The driver may make inputs later in the trip ifdesired. The driver is thus able to make a decision as to how fast, inrelation to a historical speed distribution, he/she wishes to drive on aparticular trip. The driver may make the input using a manually-operatedswitch, a touch-pad, a voice command, or any other known method(s).

At block 220, the system may assess and consider factors relating to thedriver's condition that may impact her/his ability to drive safely at aparticular speed. For example, a driver drowsiness detection system mayevaluate the driver's alertness level. Known methods for drowsinessdetection monitor behaviors such as blinking, fidgeting, head nodding,etc. Similarly, a level of driver distraction may be evaluated bydetecting whether the driver is using systems such as an entertainmentsystem, navigation system, telephone, or other systems and/or controlsof the vehicle. If the assessment of driver condition indicates that alower speed should be driven, this may be used in the determination ofthe desired relationship with the speed profile.

At block 230, physical conditions of the vehicle that may have an impactupon safe driving speed may be assessed. Examples of such conditionsinclude, but are not limited to, tire tread wear, brake wear, and otherany other mechanical or electrical fault that may be indicated byfailure of a test administered by an on-board diagnostics (OBD) system.

At block 240, driving conditions external to the vehicle may be assessedfor their impact on safe driving speed. Examples of such drivingconditions are reduced friction (mu) of the driving surface caused byrain, snow, mud or other conditions, and reduced visibility such as maybe caused by darkness or rainy conditions. Another indicator of drivingcondition may be the time-of-day as it relates to heavy traffic weight,such as during rush hour. The time-of-day may, as discussed above, betaken into account in selection of the speed profile accessed at step130. However, darkness and/or traffic conditions related to time-of-daymay also be assessed separately at this step.

At block 250, a desired differential from the speed profile iscalculated considering any one or more of the inputs or factorsdiscussed in relation to steps 210-240 above. The driver input factor atstep 210 may completely or partially override the factors in steps220-240 if desired, or any other order of preference may be establishedin the vehicle system. In any event, at step 250 it is determined atwhat point or speed along the selected speed profile the vehicle isdesired to travel.

It is possible for the differential determined and used to varydepending on the type of road segment. The type of road segment may beidentified by one or more characteristics such as curvature, incline,bank angle, camber, surface quality, and/or posted speed limit. Forexample, a driver's driving history may shows she/he drives at somewhatfaster then the mean speed of a speed profile when the segment isrelatively straight, but somewhat below the mean speed of a speedprofile when the segment is more curved). In such a case, thedifferential for relatively straight segments may be “one sigma abovemean” (assuming a normal distribution as presented in the FIG. 2example), while the differential for curved segments may be “one sigmabelow mean” on curved.

It is to be understood that the mean and sigma (standard deviation) inthe above discussion are by way of example only. The distributions,speed profiles, and differentials discussed above may be analyzed and/orcalculated from the historical data using any appropriate type ofstatistical distribution or relationship.

FIG. 5 shows an alternative method of determining a desired relationshipbetween an approaching segment speed profile and a desired target speed.At block 310 a baseline road segment is identified over which thevehicle (or vehicle/driver combination) has previously traveled and forwhich a past speed traveled by the vehicle is known. The baseline roadsegment may be selected based on similarity to the approaching roadsegment, considering factors such as curvature, incline, bank angle,camber, surface quality, and posted speed limit. If the vehicle haspreviously travelled over the approaching segment, then the approachingsegment may be identified/selected as the baseline road segment.

At block 320, the historical speed profile of the baseline segment isaccessed, from either a remote data base or onboard storage. At block330, the past speed at which the vehicle travelled over the baselinesegment is compared with the statistical speed profile of the baselinesegment. At block 340, a speed differential is determined. The speeddifferential may be expressed as a variance or difference from astatistical mean, as an absolute speed, or as any type of statisticaldistribution as discussed in relation to the method of FIG. 4. Thisspeed differential indicates, using past speed data of the vehicle, howfast the vehicle usually travels relative to the speed profile generatedfrom other (probe) vehicle over road segments similar to the approachingsegment.

At block 350, the speed differential is applied to the speed profile ofthe approaching segment. This method has the advantage of consideringthe historic driving style of the vehicle/driver, and it may be appliedeven if the approaching segment is brand new to the vehicle/driver byselecting a baseline road segment having characteristics similar to thatof the approaching segment.

Returning now to FIG. 3, at block 150, a target speed for theapproaching road segment is identified by applying the desiredrelationship (determined at block 140) to the speed profile of theapproaching road segment. It should be noted that one or more of thefactors and/or considerations discussed in relation to blocks 210-240 ofFIG. 4 may be considered in combination with the methodology of FIG. 5in order to arrive at a target speed. That is, even if the FIG. 5 methodshows that the past speed of the vehicle/driver over a baseline roadsegment is high relative to a speed profile, the target speed may beadjusted downward if driver condition, vehicle condition, and/orexternal driving conditions indicate such a speed reduction.

It should be understood that the target speed is neither a “maximumsafe” nor a “maximum comfortable” speed. Such terms necessarily relateto a known and specific geometry of the approaching road segment(features such as curve radius and bank angle) and a lateralacceleration that the vehicle will sustain when rounding a curve at agiven speed. The target speed determined in this method does not takeinto account the geometry of the approaching road segment, but ratherrelies on the speed profile generated from historical data gathered fromprobe vehicles. This allows the use of a digital map that may not beaccurate enough to rely upon to calculate road curvature and bank angleand hence lateral acceleration.

At block 160, one or more vehicle dynamic conditions are detected,including, for example, current vehicle speed and/or currentlongitudinal acceleration. At block 170, the vehicle dynamic conditionsfrom block 160 are analyzed relative to the target speed to determinewhether the vehicle is or is likely to exceed the target speed over theapproaching road segment. Other factors may be included in making thistarget speed comparison, such as an available deceleration distancebetween the current vehicle position and the approaching road segmentand/or an allowable vehicle deceleration rate. Another factor that maybe considered is the historic driving style of the vehicle/driver. Forexample, the “typical” braking rate and/or pattern of the driver whenapproaching a curve like the approaching segment may be considered. Manyother factors may be included in the decision made at block 170, forexample, road surface conditions (wet/dry/icy), and vehicle dynamicsconditions in addition to current velocity and acceleration, assumingthat the vehicle is equipped with sensors to detect such factors. Amethod of

If the vehicle is determined to be unlikely to exceed the target speedwithout any unusual action taken by the driver (block 170 “NO”), themethod returns to block 110. If the vehicle is determined to be likelyto exceed the target speed (block 170, “YES”), the method progresses toblock 180 and one or more vehicle systems are activated. Possiblevehicle systems that may be activated will be discussed below inrelation to FIG. 6.

It should be noted that in most cases the desired relationship andtarget speed will be determined for a specific driver/vehiclecombination. As such, any reference to a vehicle may be taken to referto the driver/vehicle combination when appropriate. The identity of aparticular driver driving a vehicle may be communicated to the vehiclesystem by a personalized key, key fob, RFID “smart” card, or similarknown devices. Alternatively, the driver may be identifiedbiometrically, or may be make an input (manually, voice recognition,etc.) identifying himself/herself prior to operating the vehicle.

FIG. 6 depicts a functional block diagram of a system for monitoring thespeed of a vehicle and implementing the method(s) described hereinabove.The computational module, generally indicated at 20, is preferablycarried onboard the vehicle and may comprise a microprocessor-based unitsuch as a computer having a central processing unit, memory (RAM and/orROM), and associated input and output buses. The computational module 20may be an application-specific integrated circuit or other logic devicesknown in the art. The computational module 20 may be a portion of acentral vehicle main control unit, an interactive vehicle dynamicsmodule, a main safety controller, or may be a stand-alone controller asshown.

Computational module 20 is shown sub-divided into a target speedanalysis module 20 a and a speed comparison module 20 b. This functionaldivision of the module is, however, only for ease and clarity ofdescription and is not to be construed as limiting the possibleconfiguration of the module in any way.

A driver input unit 22 is in electronic communication with computationalmodule 20 and may comprise a control and/or display device with whichthe driver may make an input indicating a desired relationship with thespeed profile. The same control/display device be also prompt the driverto make such an input at appropriate times.

One or more driver condition sensors 24 are in electronic communicationwith computational module 20. Driver condition sensors 24 may, asdiscussed above, monitor and assess driver fatigue, alertness,drowsiness, and/or distraction by known techniques.

One or more road/environmental condition sensors 26 are in electroniccommunication with computational module 20 and monitor/assess conditionsexternal to the vehicle such as road surface condition, weatherconditions, etc.

Vehicle conditions sensors 28 may, as described above, monitor andassess various vehicle systems such as tire wear and on boarddiagnostics (OBD) test results.

A road segment speed profile module 30 may comprise a wireless interfacewith a remote database (via satellite 32 and/or ground-based antenna 34)and/or an onboard electronic storage medium. Road segment speed profilemodule 30 provides access to speed profile data associated withapproaching road segments and/or baseline road segments.

A GPS navigation system 36 is also interfaced with the computationalmodule 22 to provide location and/or vehicle dynamics measurements.

Vehicle dynamics sensors 38 provide computation module 20 withinformation regarding the vehicle's current dynamic state, such as speedand acceleration.

Computational module 20 and, in particular, target speed analysis module21 a, receive inputs from appropriate systems to allow determination ofa target speed for the approaching road segment. Comparison module 20 bconsiders the appropriate factors to determine whether or not thevehicle/driver is likely, without an intervention of some type, toexceed the target speed over the approaching segment.

A driver alert system 40, a braking control module 42, and a power traincontrol module 44 are in electronic communication with computationalmodule 20. One of more of these systems may be activated ifcomputational module 20 determines that the vehicle is likely to exceedthe target speed. Driver alert system 40 may be activated to providevisual, audible, haptic and/or any other appropriate alert to the driverso that he/she may take action to reduce the vehicle speed over theapproaching segment. Braking control module 42 and/or power traincontrol module 44 may be activated to provide automatic interventions toreduce vehicle speed.

While exemplary embodiments are described above, it is not intended thatthese embodiments describe all possible forms of the invention. Rather,the words used in the specification are words of description rather thanlimitation, and it is understood that various changes may be madewithout departing from the spirit and scope of the invention.Additionally, the features of various implementing embodiments may becombined to form further embodiments of the invention.

As required, detailed embodiments of the present invention are disclosedherein; however, it is to be understood that the disclosed embodimentsare merely exemplary of the invention that may be embodied in variousand alternative forms. The figures are not necessarily to scale; somefeatures may be exaggerated or minimized to show details of particularcomponents. Therefore, specific structural and functional detailsdisclosed herein are not to be interpreted as limiting, but merely as arepresentative basis for teaching one skilled in the art to variouslyemploy the present invention.

What is claimed is:
 1. A method of monitoring the speed of an automotivevehicle comprising: operating a vehicle navigation system to determine alocation of the vehicle relative to an approaching road segment lyingahead of the vehicle; accessing a first speed profile of the approachingsegment, the first speed profile saved in a database and generated byanalyzing a statistical distribution of historical speed data collectedfrom probe vehicles that have previously travelled over the approachingsegment; identifying a baseline road segment over which the vehicle haspreviously travelled; accessing a second speed profile of the baselinesegment, the second speed profile saved in the database and generated byanalyzing a statistical distribution of historical speed data collectedfrom probe vehicles that have previously travelled over the baselinesegment; comparing a past speed of the vehicle over the baseline segmentwith the second speed profile to determine a speed differential; andapplying the speed differential to the first speed profile to establisha target vehicle speed over the approaching segment; assessing whetherthe vehicle is likely to exceed the target speed over the approachingsegment based, at least in part, on a current vehicle speed; andactivating a vehicle system to a) notify a vehicle driver of results ofthe assessment, and/or b) reduce vehicle speed.
 2. The method of claim 1wherein the baseline road segment is selected, at least in part, basedupon similarity to the approaching road segment in at least one of acurvature, an incline, a bank angle, a camber, a surface quality, and aposted speed limit.
 3. The method of claim 2 wherein the baselinesegment is the same as the approaching segment.
 4. The method of claim 1wherein the first speed profile is generated based, at least in part,upon similarity between current speed-correlated conditions andspeed-correlated conditions existing at times the historical speed datawere collected from the probe vehicles, the speed-correlated conditionscomprising at least one of a time-of-day, a day-of-week, and weatherconditions.
 5. The method of claim 1 wherein the baseline road segmentidentified is a road segment over which the vehicle has previouslytravelled when driven by the vehicle driver.
 6. A method of monitoringthe speed of an automotive vehicle comprising: operating a vehiclenavigation system to determine a location of the vehicle relative to anapproaching road segment lying ahead of the vehicle; accessing a firstspeed profile of the approaching segment, the first speed profile savedin a database and generated by analyzing a statistical distribution ofhistorical speed data collected from probe vehicles that have previouslytravelled over the approaching segment, the first speed profile beinggenerated based, at least in part, upon similarity between currentspeed-correlated conditions and speed-correlated conditions existing attimes the historical speed data were collected from the probe vehicles,the speed-correlated conditions comprising at least one of atime-of-day, a day-of-week, and weather conditions; identifying abaseline road segment over which the vehicle has previously travelled;accessing a second speed profile of the baseline segment, the secondspeed profile saved in the database and generated by analyzing astatistical distribution of historical speed data collected from probevehicles that have previously travelled over the baseline segment;comparing a past speed of the vehicle over the baseline segment with thesecond speed profile to determine a speed differential; and applying thespeed differential to the first speed profile to establish a targetvehicle speed over the approaching segment; assessing whether thevehicle is likely to exceed the target speed over the approachingsegment based, at least in part, on a current vehicle speed; andactivating a vehicle system to a) notify a vehicle driver of results ofthe assessment, and/or b) reduce vehicle speed.
 7. A method ofmonitoring the speed of an automotive vehicle comprising: operating avehicle navigation system to determine a location of the vehiclerelative to an approaching road segment lying ahead of the vehicle;accessing a first speed profile of the approaching segment, the firstspeed profile saved in a database and generated by analyzing astatistical distribution of historical speed data collected from probevehicles that have previously travelled over the approaching segment;identifying a baseline road segment over which the vehicle haspreviously travelled when driven by a driver currently operating thevehicle; accessing a second speed profile of the baseline segment, thesecond speed profile saved in the database and generated by analyzing astatistical distribution of historical speed data collected from probevehicles that have previously travelled over the baseline segment;comparing a past speed of the vehicle over the baseline segment with thesecond speed profile to determine a speed differential; and applying thespeed differential to the first speed profile to establish a targetvehicle speed over the approaching segment; assessing whether thevehicle is likely to exceed the target speed over the approachingsegment based, at least in part, on a current vehicle speed; andactivating a vehicle system to a) notify the driver of results of theassessment, and/or b) reduce vehicle speed.